Instructions to use binwang/bert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use binwang/bert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="binwang/bert-base-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("binwang/bert-base-uncased") model = AutoModelForMaskedLM.from_pretrained("binwang/bert-base-uncased") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 47f359c
upload flax model
Browse files- flax_model.msgpack +3 -0
flax_model.msgpack
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version https://git-lfs.github.com/spec/v1
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oid sha256:ea201fabe466ef7182f1f687fb5be4b62a73d3a78883f11264ff7f682cdb54bf
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size 438064459
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